Google Engineering Lead AI & Data
AccenturefederalservicesRole Overview
Accenturefederalservices is hiring a Google Engineering Lead AI & Data. This is a full-time role in Washington. Full responsibilities, required qualifications, and the apply link are listed in the description below.
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Job description
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Accenture Federal Services (AFS) is seeking a Google Engineering Lead to join our AI & Data Practice. This high-visibility role is designed for a technical leader who excels at the intersection of pre-sales strategy, enterprise-scale architecture, and hands-on engineering execution. In this capacity, you will serve as the lead engineer for our GTM initiatives with Google, driving the technical vision for new federal pursuits. You will be responsible for both the high-level architectural strategy in client-facing environments and the hands-on leadership of engineering teams developing functional prototypes.
Key Responsibilities
- Strategic GTM Enablement: Collaborate with practice and account leaders to identify emerging federal market requirements and translate them into robust, GCP-native solution offerings.
- Solution Architecture & Design: Serve as the Lead Solution Engineer for new opportunities. You will be responsible for designing end-to-end, secure, and scalable architectures that integrate the breadth of Google’s ecosystem – including but not limited to Google's Gemini models, Vertex AI Model Garden, BigQuery, and and Agent Builder.
- Pre-Sales Technical Leadership: Lead technical discovery and solutioning for high-priority federal pursuits. Act as the primary Subject Matter Expert (SME) during client workshops to articulate the value and feasibility of Google Cloud technologies.
- Rapid Prototyping Lead: Direct the end-to-end development of Proofs of Concept (PoCs) and prototypes. This includes defining the technical roadmap, selecting the appropriate GCP services, and serving as the lead engineer to ensure a successful "build" for pursuit-related milestones.
Professional Qualifications
- Extensive Experience: A minimum of 10 years of experience in systems engineering, cloud architecture, or technical consultancy, with a minimum of 4 years of specialized expertise in Google Cloud Platform (GCP).
- Enterprise Solution Architecture: Proven ability to design holistic, multi-service architectures that solve mission-critical federal challenges. You must be able to navigate trade-offs between cost, performance, and security while ensuring alignment with the client's long-term digital transformation goals.
- Innovation-Led Pre-Sales Expertise: Proven success as a lead engineer in the end-to-end lifecycle of high-fidelity prototypes that drive market interest. This includes:
- Translating complex federal mission challenges into functional, tangible GCP solutions.
- Designing and executing "North Star" demonstrations that illustrate the future state of a client’s environment.
- Leading the "Proof of Value" phase by building functional software, data pipelines, or AI models that validate AFS’s technical differentiators to senior federal stakeholders.
- Engineering Proficiency: Advanced, hands-on experience in developing and deploying cloud-native applications and data pipelines. Deep technical expertise in Vertex AI, CCAI, GKE, and BigQuery is highly prioritized.
- AI/ML Lifecycle Expertise: Proven experience designing, developing, and deploying production-grade AI/ML solutions and architectures including LLM-based applications, computer vision, Agentic AI, and RAG.
- Federal Domain Knowledge: Comprehensive understanding of the federal IT landscape, including security requirements (FedRAMP/ATO processes), legacy application landscape, and procurement cycles.
- Team Leadership: Experience guiding multi-disciplinary engineering teams through the rapid development of high-fidelity prototypes to support new opportunities.
Education and Certifications
- Bachelor’s degree in Computer Science, Engineering, or a related technical field.
- Required: Google Cloud Professional Cloud Architect.
- Preferred: Additional certifications in Google Cloud Data Engineering, Security, or Machine Learning.
The Extras:
- US Citizenship Required
As required by local law, Accenture Federal Services provides reasonable ranges of compensation for hired roles based on labor costs in the states of California, Colorado, Hawaii, Illinois, Maine, Maryland, Massachusetts, Minnesota, New Jersey, New York, Vermont, Virginia, Washington, and the District of Columbia, and the city of Cleveland. The base pay range for this position in these locations is shown below. Compensation for roles at Accenture Federal Services varies depending on a wide array of factors, including but not limited to office location, role, skill set, and level of experience. Accenture Federal Services offers a wide variety of benefits. You can find more information on benefits here. We accept applications on an on-going basis and there is no fixed deadline to apply.
About Accenturefederalservices
Accenturefederalservices
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Frequently Asked Questions
How do I apply for the Google Engineering Lead AI & Data position at Accenturefederalservices?
Use the Apply button above to submit your application directly to Accenturefederalservices. Most applications take less than 5 minutes if your resume and contact details are ready, and you'll be routed to the employer's official application system to finish.
Where is the Google Engineering Lead AI & Data position at Accenturefederalservices located?
This position is based in Washington. Accenturefederalservices has not indicated remote or hybrid options for this role, so candidates should plan for on-site work.
What does a Google Engineering Lead AI & Data at Accenturefederalservices earn?
Accenturefederalservices has not disclosed a salary range in this posting. Many employers share specifics later in the interview process; you can also ask during a recruiter screen if compensation transparency is important to you.
When was the Google Engineering Lead AI & Data role at Accenturefederalservices posted?
This role was posted on June 8, 2026 (31 days ago). It's still listed as actively hiring; we re-confirm openings against the source system multiple times per day and remove closed roles.
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